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Abstract— A prototype microwave breast imaging system is

used to scan a small group of patients. The prototype implements a monostatic, radar-based approach to microwave imaging and utilizes ultra-wideband signals. 8 patients were successfully scanned, and several of the resulting images show responses consistent with the clinical patient histories. These encouraging results motivate further studies of microwave imaging for breast health assessment.

Index Terms—microwave breast imaging, radar imaging, ultra-wideband radar, patient study

I. INTRODUCTION icrowave-frequency imaging techniques have been

proposed as complementary methods for breast imaging. Active microwave imaging methods include tomography, in which maps of the electrical properties of the tissues are formed (e.g. [1-3]), and radar, which is used to create images indicating the presence and location of strongly scattering objects (e.g. [4-6]). The basic premise underlying both of these methods is a difference in the microwave frequency properties of healthy and malignant tissues. Recent studies examined the permittivity and conductivity of excised breast tissue samples over a broad frequency range, suggesting complex distributions of the properties of healthy tissues in the breast [7]. Specifically, fatty tissues are expected to have low permittivity and conductivity, permitting interrogation by microwaves to depths of several centimeters. Greater permittivity and conductivity are expected for fibrous and glandular tissues, resulting in reflections of microwave signals, as well as limited penetration due to increased loss. Malignancies are expected to have differences in properties on the order of 10% when compared to glandular tissues [8]; as tumors are often located in glandular tissues, this represents a significant challenge for detection and imaging of

Manuscript received October 15, 2012. This work was supported by the

former Alberta Heritage Foundation for Medical Research. E. Fear is with the Department of Electrical and Computer Engineering,

Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4 (phone: 403-210-5413; fax: 403-282-6855; e-mail: [email protected]).

J. Bourqui and C. Curtis are with the Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, Calgary ([email protected]; [email protected]).

D. Mew is with the Department of Surgery, Faculty of Medicine, University of Calgary.

B. Docktor and C. Romano are with the Department of Radiology, Faculty of Medicine, University of Calgary.

malignancies with microwaves. To address this challenge, the literature contains numerous reports of innovations in algorithms for image reconstruction [9-12], primarily tested with data collected from simulation models. While an increasing number of papers include work with experimental systems and phantom models (e.g. [13-16]), there are very few reports of prototype systems capable of testing microwave breast imaging on human subjects and fewer reports of the results of such tests.

The first prototype systems for and human tests of microwave tomography for breast imaging were reported by a group at Dartmouth College [2, 17]. The woman to be scanned lies on her stomach with her breast extending into a tank filled with a mixture of glycerine and saline. An array of 16 antennas in a circular configuration is scanned from the nipple towards the chest wall. At up to 7 vertical locations, measurements at multiple frequencies (e.g. 300 to 900 MHz [2]) are collected by exciting each antenna in turn and recording signals at other antennas in the array. A series of 2D images is created by matching measurements to data simulated with a model containing estimates of the properties. The first patient study involved 23 women with no abnormalities reported on mammograms in order to provide baseline information [18]. The mean properties of the tissues generated were compared with clinical and radiographic features. Trends such as decrease in microwave frequency conductivity with an increase in BMI were noted. A second study involved 150 women, including women with abnormal and normal mammograms [19]. Regions of interest (ROI) in one breast were defined with information extracted from other imaging modalities (e.g. mammography) and compared to ROI in the mirror image location on the other breast, as well as the mean pixel value in the images. For lesions greater than 1 cm3, significant differences in the microwave frequency conductivity of the ROI were demonstrated. More recently, extension to 3D imaging at higher frequencies (e.g. 1.3 GHz) has been reported [20]. Overall, studies of microwave tomography for breast imaging show results consistent with patient histories and demonstrate differences in conductivity of malignancies when compared to healthy tissues.

A group at the University of Bristol has reported human testing of prototype systems for radar-based breast imaging. The approach is multi-static, featuring 31 (prototype 1) [5] or 60 (prototype 2) [21] antennas distributed over a hemispherical surface. The woman to be scanned lies on her stomach with her breast extending through a hole in the

Microwave breast imaging with a monostatic radar-based system: a study of application to

patients E.C. Fear, Senior Member, IEEE, J. Bourqui, C. Curtis, D. Mew, B. Docktor, and C. Romano

M

This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.The final version of record is available at http://dx.doi.org/10.1109/TMTT.2013.2255884

Copyright (c) 2013 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing [email protected].


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examination table. The hemispherical array is placed in contact with the breast. Measurements are collected by exciting each antenna in turn and recording reflections at all other sensors. With prototype 2, the frequency range is 4 to 8 GHz and the entire breast is scanned in under 10 seconds [21]. Images are created by focusing the reflections in the volume of interest with algorithms based on a time-shift and sum approach. A procedure to reduce the dominant reflections from the skin involves collecting a second set of measurements with the array rotated by several degrees, then subtracting these results to reduce common reflections [5]. Extensive testing in phantoms has been reported, and initial reports indicate successful detection of known lesions in patients when compared with mammography [21]. Challenges identified from the clinical studies include imaging dense breast tissues, as well as ensuring consistent contact between the sensor interface and the patient [21, 22].

At the University of Calgary, we have developed a prototype system for radar-based breast imaging. Similar to the prototypes developed at Dartmouth and Bristol, the woman to be scanned lies with her breast extending through a hole in an examination table. A tank containing an immersion liquid and sensors is located under the table. The sensors include a custom ultra-wideband antenna [23] and a laser, which are both attached to an arm. The arm is used to move the sensors in the vertical direction, and the entire tank rotates. In this manner, the UWB antenna is scanned around the breast, sending and receiving microwave signals (i.e. monostatic data collection) over the frequency range from 50 MHz to 15 GHz. The recorded data are used to generate 3D images of the breast using a time-shift and sum approach [24], with the volume of interest for imaging defined by the laser data [25] and an adaptive algorithm used to reduce the dominant reflections from the skin [26]. The measurement performance of the prototype and initial tests on phantoms have been reported [6].

In this paper, the first scans of patients with the tissue sensing adaptive radar (TSAR) prototype system are described. The goal of this study was to perform an preliminary assessment of the TSAR technology for microwave breast imaging, and 8 subjects were successfully scanned. Even with the limited number of patients, we believe that this is a significant addition to the literature because it is one of the few reports of the application of microwave breast imaging to human subjects. This study differs from previous microwave breast imaging studies of patients in several ways. First, the frequency range over which data are collected is broader. Second, a laser is used to define the imaging volume, providing essential information for enhancing image reconstruction. Compared to the majority of the reported Dartmouth studies, we are testing a radar-based approach and creating 3D images. Compared to the Bristol studies, we use a monostatic system to collect data and a filtering approach to reduce the reflections from the skin. We also collect magnetic resonance scans of the breast of each patient to facilitate interpretation of the radar data.

II. METHODS The TSAR prototype system and imaging algorithms have

previously been described in detail, so brief overviews are provided. The patient recruitment and scan procedures, as well as image interpretation and analysis, are discussed in this section.

A. Prototype System The TSAR system [6] consists of a patient interface, the

sensors attached to a positioning arm and placed in a cylindrical container or tank, motors to move the arm and tank, microwave measurement equipment and cables, and custom software to control the system. Fig. 1 shows an overview of the TSAR system, while Fig. 2 provides more details on the repositioning of the sensors around the breast.

Figure 1: TSAR prototype system (from [6]).

The patient interface consists of a padded table with a hole through which the breast extends into the cylindrical container. The container is filled with canola oil (εr=2.5, σ < 0.04 S/m), which serves to reduce the reflections from the skin and permits a reduction in antenna dimensions. The sensors are located in the container and connected to a positioning arm; the arm moves up and down, and the entire tank rotates (Fig. 2). Effectively, the sensors are scanned on a cylindrical surface that surrounds the breast (Fig. 2). In the vertical direction, the sensors may be scanned from 24 mm to 141 mm below the top of the lid of the container. The lid contains a circular opening through which the breast extends. The opening has a radius of 65 mm and the tip of the sensor is 70 mm from the center of the opening.

For this study, a BAVA-D antenna [23] is attached to the positioning arm and connected to a vector network analyzer (8722ES, Agilent Technologies, Palo Alto, CA, USA) which is used to collect the microwave measurements. The BAVA-D operates over the frequency range from 2.4 GHz to over 15 GHz (S11 better than -10 dB). At a distance of 2 cm from the aperture, the half-energy beamwidth is 2.3 cm in the horizontal direction and 4.2 cm in the vertical direction. At this distance, the fidelity, which describes the similarity of the field to the desired radiated pulse, is 96%. We note that the cylindrical scan pattern results in significant differences in separation between the breast and antenna during a patient




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scan. A laser is also attached to the positioning arm, and the laser

data are used to estimate the surface of the breast [25]. A camera is attached to the side of the tank in order to provide visual feedback of the antenna location relative to the breast during the scan. The images from the camera are also used to design the patient scan pattern.

(a)

(b)

Figure 2: Details on sensor repositioning (from [6]) (a) Top-down view of the lid with hole through which the breast extends. The antenna and laser are attached to an arm, and the repositioning of the antenna in the horizontal plane is also shown. (b) The laser and antenna are scanned around the breast as the tank rotates. The arm also moves vertically. This effectively results in the antenna being positioned over a cylindrical surface during a scan. The dots indicate the location of the antenna tip during measurements.

A patient scan involves collecting measurements at up to

200 locations around the breast. The extent of the breast in the vertical direction is approximated using the digital images. The number of rows (vertical locations where data are collected) is defined, with separation between rows ranging from 5 to 10 mm. The number of antenna locations per row is calculated to ensure that the total number of locations per breast is 200 or fewer. The number of rows, separation between rows and number of antennas per row are provided for each patient in Table 1.

At each antenna location, microwave measurements are collected with a port power of -5 dBm and at 1601 points over the frequency range from 50 MHz to 15GHz. To reduce the noise floor, an intermediate frequency (IF) bandwidth of 1 kHz and averaging over 3 frequency sweeps are incorporated into the measurement protocol. The same settings are used to collect measurements for all patients. With the antenna repositioning and collection of measurements, a scan of one

breast takes less than 30 minutes. The measurements are collected in the frequency domain,

however image formation is performed with time-domain signals. Measurements are converted to frequency by weighting the measured data with the spectrum of a differentiated Gaussian signal, then transforming the resulting data to the time-domain via an inverse chirp-z transform [27]. The differentiated Gaussian signal has full-width half-maximum frequency content from 1.3-7.6 GHz and a center frequency of 4 GHz .

Prior to the patient scan, the system is warmed up and measurements are collected with an empty tank. After the patient scan, the empty tank is scanned again with the same set of antenna locations as used during the patient study. The scans of the empty tank are used to calibrate the data. Specifically, the signals collected with the empty tank are subtracted from the signals collected with the patient present. In [6], the repeatability of positioning is examined, and we expect the antenna locations in the calibration scan to be within +/- 0.1 mm and +/-0.1 degree of the locations in the patient scan.

B. Imaging The calibrated data are pre-processed prior to forming an

image. First, dominant reflections are received from the skin and must be reduced in order to permit imaging the interior of the breast. This is achieved with a neighbourhood-based approach to estimating the skin reflection [26]. Specifically, a target antenna is selected. Antennas that illuminate a similar region of the breast to the target antenna are identified; the signals recorded at these antennas are filtered in order to estimate the signal at the target antenna. In addition to removing reflections from the skin, common reflections (i.e. clutter) tend to be reduced as well.

Next, images are formed by focusing the pre-processed data. The ROI for focusing is defined by the laser surface estimate of the breast [25]. This surface estimate permits calculation of the path lengths in the immersion liquid and the breast interior. The paths in each material are used to estimate the travel time from each antenna to a focal point of interest. This process is repeated for each antenna in the array, and the corresponding components of each signal are selected and summed to provide the contribution to the image at the focal point location. To form a 3D image, the focal point is scanned through the ROI. Finally, the data are squared. Therefore, the contribution to the image at each location is:

(1) where τn(x) is the estimated travel time from antenna position n to focal point x and sn(t) is the value of the signal at a selected time recorded at position n. We note that, for the patients in this study, the properties of the breast interior are not known and an average permittivity of εr=9 is used to estimate travel times. While each patient image incorporates patient-specific antenna locations and laser surfaces, one




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version of the image reconstruction code is used to create the images (i.e. there are no additional patient-specific parameters in the code).

The responses in the image roughly correspond to the energy of the reflections originating at the focal point. The TSAR imaging algorithm has been tested through application to simulated and measured data collected from phantoms (e.g. [6, 28]), demonstrating detection and localization of inclusions.

C. Patient recruitment and scanning To date, the TSAR prototype has been used to image 9

patients (study E-22121 approved by the Conjoint Health Research Ethics Board at the University of Calgary). The patients were recruited into the study during appointments at the Breast Health Clinic, Foothills Medical Centre, Calgary, AB by Dr. D. Mew. Criteria for patient recruitment were partly informed by the configuration and scanning approach used with the TSAR scanner. Specifically, patients had breast size corresponding to B or C cup and suspicious areas in the breast that were not located in the axilla region. Because of the cylindrical scan pattern, lesions in the axilla area would not be effectively imaged. Breast sizes of B or C cup were included due to the dimensions of the scanning region and size of the opening in the tank. Finally, eligibility for an MR scan (e.g. no metallic implants) was also considered.

To aid in interpreting TSAR data, each patient had a contrast-enhanced MRI scan on a 1.5 Tesla Siemens Sonata MR Scanner equipped with breast coils. The MR scan was performed according to standard clinical practice at the Foothills Hospital in Calgary. For comparison with microwave images, we select MR images obtained with a T1-weighted sequence (Gradient Echo VIBE with variant SP/OSP). With this sequence, fat is suppressed and glandular tissue has higher pixel intensity. Both pre-contrast scans and subtracted images are inspected. The MR scan was performed prior to the TSAR scan; one patient had both scans on the same day, 4 patients had TSAR scans within 2 days of the MR scans, 2 patients had TSAR scans within 4 days and the final patient had a TSAR scan 12 days after the MR scan. In the majority of cases, the patients recruited into the study had a suspicious lesion previously identified in one breast through mammography or clinical examination. Therefore, the breast with the suspicious region was scanned with TSAR.

The TSAR scan was performed with the assistance of a registered nurse. A research engineer operated the scanner from behind a privacy curtain. The nurse assisted the patient with positioning on the scanner. The location of the breast in the scanner was initially assessed by viewing digital images collected as the scanner was repositioned around the breast. If the breast was not reasonably centered in the scanner, then the nurse would assist the patient with repositioning slightly. The digital images were also used to design the scan pattern, as described in Section II.A. The images were also used to detect patient movement. Movement was only observed in one case, as the patient shifted position slightly on the scanner. We note that the patient interface is designed to support the chest of the

patient while the breast extends into the scanner. Therefore, significant movement is not anticipated unless the patient is repositioned. Finally, each patient was interviewed by the nurse in order to collect feedback on their experience (e.g. comfort, pressure points, immersion liquid).

For each patient, additional clinical information was accessed in order to provide complete case histories. This information included the most recently acquired mammograms, any ultrasound studies, and reports on all images. When biopsies and/or surgical resections were performed, pathology reports were also accessed.

D. Image interpretation and analysis After all data were collected, the cases were discussed with

clinical collaborators (Drs. Mew, Romano and Docktor). This included review of mammograms, MR scans and clinical reports to identify the presence, location and type of any lesions. The clinical team also reviewed the TSAR images for correspondence between known clinical histories and responses in the TSAR images.

As mammograms, MR scans and TSAR images are taken with the breast in different configurations, direct comparison of images is not possible. Specifically, mammograms are two 2D images of the breast during compression, MR scans are acquired with the breast extending into the breast coil, and the breast floats in the immersion liquid during TSAR scans. Therefore, the breast appears to be different shapes and sizes during the 3 scans. The o’clock position of lesions is typically included in clinical reports, so the o’clock location of responses in the TSAR images are noted for comparison with clinical reports. To aid in interpretation of images, TSAR images indicate orientation in terms of waist-to-head and left-to-right. The images in the coronal plane are looking at the patient, such that the o’clock position is the same as per clinical work.

Due to the small number of subjects in the study, limited quantitative analysis of results is performed. The mean values of region-of-interests (ROI) containing the significant responses are calculated, and compared to the average of the remaining pixels in the image. ROIs are identified as responses that are at least 50% of the maximum response in the image. The mean values are calculated by first defining a volume of interest for each ROI as the full-width half-maximum response in the x, y and z directions. The mean is calculated by selecting pixels in the ROI with values greater than 0.5 of the maximum response. The mean of all pixels excluding the ROIs is also calculated. By comparing the mean value of the ROI to the mean of all other pixels, a signal-to-clutter ratio (SCR) is calculated. This metric provides preliminary insight into detection capabilities.

III. RESULTS One of the 9 patients was not successfully imaged because

the scanner was not able to accommodate the breast; recruitment criteria were subsequently changed to include B and C cup sizes. Table 1 provides an overview of information related to the 8 patients who were scanned with TSAR,




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indicating that the volunteers for the study included a range of clinical cases.

TABLE 1: SUMMARY OF PATIENT INFORMATION Patient Age Breast

imaged # of rows

Row separation (mm)

Antennas per row

Breast density Disease Group

1 32 L 6 10 30 Heterogeneous No disease C 2 47 L 9 5 20 Not classified Post-biopsy B 3 64 L 8 10 20 Extremely dense Benign A 4 53 R 6 5 30 Heterogeneous Malignancy A 5 35 L 9 8 20 Scattered/heterogeneous Malignancy A 6 42 L 9 5 20 Heterogeneous Post-biopsy B 7 44 L 8 7 20 Heterogeneous No disease B 8 47 R 5 5 30 Heterogeneous Post-biopsy C

For patients 3, 4 and 5, clinical images clearly identified

malignant or benign lesions and there is little ambiguity about the extent and location of disease. We refer to these patients as group A. For patients 2, 6 and 8 (group B), patients had multiple suspicious regions that in some cases were removed via biopsy prior to TSAR imaging. Finally, patients 1 and 7 (group C) did not have breast disease. Each of these groups of patients is discussed in turn.

A. Group A 1) Patient 4

A 10 mm diameter mass at the 4 o’clock radian of the right breast was identified through mammography. MR imaging showed the lesion at 5 o’clock and also detected a second, possibly benign lesion at 7 o’clock. Post-surgical pathology indicated that the first lesion was grade II/III metaplastic carcinoma. No mention was made in the pathology report of the second lesion. Fig. 3 contains two different imaging planes extracted from the MR scan, clearly showing the location of the malignant lesion. TSAR images (Fig. 4) show responses consistent with the benign and malignant lesions, as well as responses corresponding to a concentration of glandular tissues (near 11 o’clock). The signal-to-clutter ratio calculated for the dominant response in the image is 5.43 dB. The SCR for the response near the location of the benign lesion is 3.97 dB, while the response near 11 o’clock has an SCR of 3.93 dB.

2) Patient 5 The mammogram of the left breast of this patient showed

extensive micro-calcifications in the lateral aspect around 3 o’clock. Biopsy indicated invasive ductal carcinoma (IDC) with high-grade carcinoma in situ. MR images showed enhancement from 2 to 6 o’clock in the left breast, as well as a focal mass located above the nipple (Fig. 5). Post-mastectomy pathology indicated a region of 4x2x2 cm of IDC in the upper outer quadrant of the breast.

The maximum responses in the TSAR images (Fig. 6) appear as “ringing” above the nipple. The SCR for the two dominant responses are 4.9 and 4.67 dB. These responses may correspond to the focal mass located above the nipple. The region of IDC is located near to the chest wall, so perhaps the bulk of the mass did not extend into the scanned region, as it begins 2.4 cm below the top of the tank lid. There is also padding on the table and lid, and the breast floats in the oil. Therefore, it is difficult to predict whether the region of the

breast containing the IDC was actually imaged during the TSAR scan. Another possibility is that the algorithm used to reduce reflections from the skin also reduced reflections from the region containing IDC, as antennas would likely see similar responses. Finally, the breast is 12 cm diameter and noted to be heterogeneously dense. Therefore, this is a challenging case for microwave breast imaging.

3) Patient 3 The left breast of this patient contained a fibroadenolipoma of several centimeters diameter. The breast tissue is noted as extremely dense on the mammography report and the mass is contained in the inner lower quadrant of the left breast. The mammogram is shown in Fig. 7, and TSAR images are shown in Figs. 8 and 9. The TSAR images in Figs. 8 and 9 are formed with different thresholds used to detect and filter the dominant skin response. With a lower threshold, differences in the reflections near the benign lesion are preserved after filtering, and a response is noted in the inner lower quadrant of the breast. While this is a desired result due to the known location of the fibroadenolipoma, the higher threshold results in more consistent skin response identification.

(a) (b)

Figure 3: MR image of patient 4. A pre-contrast series is subtracted from a post-contrast series of images, as per standard clinical practice. (a) An image in the sagittal plane showing the lesion in the lower quadrant of the breast. (b) An image in the coronal plane is obtained from the resulting data set.




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Figure 4: TSAR images of patient 4. The image on the lower left is in the same orientation as the MR image in Fig. 2.

Figure 5: MR scan of the left breast of patient 5. The images are the difference between pre- and post-contrast scans. (a) The region of IDC in the upper outer quadrant of the breast. (b) The focal mass above the nipple.

Figure 6: TSAR images of patient 5 show response above nipple.

Figure 7: Mammogram (medial-lateral oblique – MLO – view) of patient 3 showing fibroadenolipoma.

Figure 8: TSAR images of patient 3 formed with a higher threshold used to define filter coefficients for reducing the skin reflection.

Figure 9: TSAR images of patient 3 formed with a lower threshold used to define filter coefficients for reducing the skin reflection.

B. Group B This group contains 3 patients with multiple lesions located

in several regions of the breast. The patients had biopsies at least 2 weeks prior to the TSAR scan. Therefore, interpreting TSAR images is very challenging for these cases, as there are biopsy sites in addition to any remaining lesions.

1) Patient 2 The left breast of patient 2 was suspected to contain both a

benign and a malignant lesion. With ultrasound, the benign




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lesion was identified at 1 o’clock, while the suspicious lesion was located at 11 o’clock. Biopsy indicated that this lesion was IDC with extension into fatty tissue and a small ductal carcinoma in situ (DCIS) component. Biopsy had been performed prior to the MR and TSAR scans, and a clip left in place to mark the location. No malignant cells were found near the clip after mastectomy, however a benign lesion was identified in the upper outer region of the breast and at 1 o’clock in addition to the biopsy site near 12 o’clock. Fig. 10 shows a diagram of the information from images and reports. The TSAR images in Fig. 11 show several responses, including a weaker response near the original site of the malignancy. The SCR for the first 4 peaks in the image are 4.63, 4.00, 3.32 and 3.05 dB, illustrating the similarities in the responses distributed throughout the image. This is a difficult case to interpret due to the significant clutter in the TSAR images, combined with the complexity of the clinical history.

Figure 10: Diagram of information from images and reports for patient 2

Figure 11: TSAR images for patient 2

2) Patient 6 This patient had an area of opacity superior to the left nipple

and 5 mm in diameter identified on a mammogram. Supplementary views revealed a cluster of micro-calcifications. A biopsy was performed, and the micro-calcification cluster (located in the upper inner quadrant at about 11 o’clock) was almost completely removed and a marking clip put in place. The biopsy indicated DCIS of about 0.5 cm in diameter. On a subsequent MR scan, the biopsy clip with focal enhancement was detected, however no significant enhancement was noted near the site. A second lesion at 4 o’clock of 8-9 mm diameter was detected, and suggested to be a myxoid fibroadenoma. Post-surgical biopsy

revealed no residual DCIS, however proliferative breast disease without atypia was noted. Fig. 12 shows a diagram of the information from images and reports, while Fig. 13 shows the TSAR images. Two responses are noted in the lower region of the image, and have SCR of 6.07 and 1.69 dB. In this case, it is unlikely that the response corresponds to the fibroademona, as only the lower part of the breast was scanned with TSAR, and the region containing the fibroadenoma was likely not included in the scanning region.

3) Patient 8 This patient reported a lump in her right breast in the 3-4

o’clock position. Mammography revealed micro-calcifications in the retroareolar region with one cluster located 18 to 20 mm above and slightly lateral to the nipple in the anterior third of the breast at 11 o’clock; a second focus of micro-calcifications is also possible. Biopsy of the area with micro-calcifications (12 o’clock) indicated high grade DCIS. The MR scan showed an area of subtle enhancement in the upper outer quadrant of the right breast consistent with the biopsied region. The biopsy clip may also be identified via an artefact in the image. Post-mastectomy pathology reported 2 regions “under” the nipple region of DCIS. Fig. 14 presents the mammogram of the patient and illustrates the information from reports and images, while Fig. 15 contains TSAR images. TSAR images show responses that may correspond to two regions of DCIS, which were previously undetected by both MR and mammography. It is possible that a response is also obtained from the biopsy location. The SCR of the two dominant responses are 5.95 and 5.79 dB, while the response near the biopsy site has an SCR of 2.35 dB.

Figure 12: Diagram of information from images and reports for patient 6





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(a) (b)

Figure 14: (a) Mammogram of patient 8 (b) Diagram of clinical reports.


C. Group C The 2 patients in this group do not present with breast

disease that may be imaged with TSAR. In one case, TSAR is not expected to be sensitive to the benign lesions. In the other case, no lesions are present.

1) Patient 7 This patient reported an area of tenderness in her right

breast and mammograms showed several benign lesions. Subsequent mammography and ultrasound studies showed a lesion in the left breast at 10 o’clock with 11 x 7 mm dimension and near 2 cysts. Pathology determined this to be benign breast tissue with fat necrosis. TSAR images (Fig. 16) show one response that does not correspond to the necrosis. The SCR for the 4 largest responses in the image range from 2.65 to 5.04 dB.

2) Patient 1 This patient had no known history of breast disease.

Mammograms identified the breasts as heterogeneously dense. This breast has a small amount of glandular tissue on the inner side and more glandular tissue on outer side. The MR scan detected an unidentified lesion in the left breast at 4 o’clock, however the lesion was not apparent on mammography or found on a follow-up ultrasound or on a second follow-up MR scan. The TSAR images in Fig. 17 show a dominant response (SCR of 7.04 dB) on the inner side, perhaps due to the concentration of glandular tissue mentioned in the imaging

report.

Figure 16: TSAR images for patient 7.


IV. DISCUSSION The patients with little ambiguity about the presence and

location of lesions (group A) showed clear detection in the case where this was expected, namely patient 4. A response was also detected for patient 3, which is intriguing because of the significant size and type of the lesion. For patient 5, responses that may correspond to a focal lesion of IDC were evident, however the breast contained extensive disease that may not have extended entirely in the imaging region. A patient interface and scanning technique that adapt to a range of breast sizes and provide the capability to image the entire breast would permit better assessment of the TSAR approach to microwave breast imaging.

In group B, the clinical cases were more complex and involved removal of malignancies via biopsy prior to imaging. In mammography, clusters of micro-calcifications typically indicate worrisome areas that are then recommended for further investigation. During biopsy, an 11-gauge needle is usually used at Foothills Hospital. For two patients in our




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study (patients 2 and 6), this resulted in the removal of the micro-calcification clusters and the associated malignant cells (as demonstrated later via post-surgical pathology). For patient 8, DCIS was removed via biopsy, however 2 regions of DCIS remained in the breast during the TSAR scan; responses in the TSAR images are consistent with the location of these regions. For these three cases, the suspicious regions are subtle and challenging to detect with mammography and MRI, as well as TSAR. However, TSAR does appear to have detected DCIS in one case that was only found during post-mastectomy histology. The sensitivity of MRI to DCIS is limited, and it is of interest to explore the sensitivity of TSAR to DCIS. This involves imaging patients prior to biopsy, which will be considered during a follow-up patient study.

In group C, one patient does not have breast disease and one patient has a lesion that was diagnosed as fat necrosis. TSAR is not expected to be sensitive to fat necrosis, as fat is typically translucent to microwaves. For these patients, the TSAR images showed responses, however these responses are smaller in magnitude than the responses detected for patients in group A. This suggests additional studies to investigate the possibility of a threshold to delineate between responses corresponding to malignancies and other responses, perhaps through comparison of responses detected for right and left breasts.

Overall, the preliminary application to patients of microwave breast imaging with a monostatic radar-based approach is encouraging. While not all lesions were detected, several responses consistent with clinical histories are identified in TSAR images. Challenges encountered when interpreting images included reconciling TSAR images with clinical data due to the differences in orientation of the patients with different imaging modalities, as well as the presence of multiple responses in images. The patients provided generally very positive feedback on the scan (e.g. comfort level, time), and also identified several areas for improvement. Combined with the experience of scanning human subjects and working with data and images, this feedback has allowed us to identify several key areas for improvement.

An adaptive approach to scanning is planned for the next-generation prototype system. This involves positioning the antenna such that it is located at a consistent distance away from and orientation relative to the breast. This adaptive positioning is expected to permit scanning a range of breast sizes, as well as the entire breast. With the current prototype, the separation between the breast and antenna may vary from 1 cm to several cm over the scan. With consistent separation, we anticipate consistent reflections from the skin, leading to more effective filtering of these clutter responses. The current prototype has sensitivity of -80 dB [6], which may not be sufficient to measure some of the signals generated by malignant tissues, especially with significant separation between the antenna and breast. Therefore, adaptive scanning is expected to result in greater flexibility for imaging, as well as increased consistency between signals and more effective use of the dynamic range of the measurement system.

Key improvements to the imaging algorithms have been identified for future work. First, an average relative permittivity value of 9 is used for the breast interior when forming images. The patients in this study typically had heterogeneously dense tissues, which are expected to have greater average properties. Patient-specific methods to estimate average properties are expected to improve images. To this end, we are developing estimation of average properties through transmission measurements [29], as well as region-based microwave tomography [30]. The results for patient 3 show differences in results based on the filter used to suppress the skin response, likely because the lesion is located close to the skin. Further investigation of the performance of the imaging algorithm with lesions located close to the skin, as well as deeper in the breast, is planned via studies of more complex phantoms and realistic breast models.

V. CONCLUSION This paper reports the first microwave breast imaging scans

of patients performed with a monostatic, radar-based system. The prototype system and imaging technique incorporate several key differences when compared with microwave tomography and multi-static radar systems used in previously reported patient studies [18, 19, 21]. First, the TSAR prototype system collected data over a wider frequency range, permitting inclusion of this information in imaging. However, the current TSAR prototype has sensitivity limited to approximately -80 dB and longer scan times. The sensitivity is particularly important, as reflections from smaller or deeper lesions may be below the sensitivity limits of the system. The TSAR approach to imaging also included use of a laser to estimate the surface of the breast, and this estimate was not only useful for imaging but also for reconciling the TSAR images with the extensive clinical data available for each patient.

The patient study was limited to 8 subjects and covered clinical cases ranging from patients with clearly defined presence and location of disease to complex cases with multiple benign and malignant lesions and breasts without disease. In spite of the complexities and limitations of the prototype system, several TSAR images exhibited responses consistent with clinical histories. These intriguing results motivate a follow-up patient study. We plan to incorporate an improved prototype system and imaging algorithms that address issues identified during the scans of patients described in this paper in order to provide clearer insight into the potential clinical role of microwave breast imaging.

ACKNOWLEDGMENT The authors would like to acknowledge Dr. Trevor

Williams for his contributions to signal and image processing, and Dr. Richard Frayne for his contributions to the MR imaging component of this work.

REFERENCES




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[1] D. W. Winters, et al., "Three-Dimensional Microwave Breast Imaging: Dispersive Dielectric Properties Estimation Using Patient-Specific Basis Functions," IEEE Trans Med Imaging, vol. 28, pp. 969-981, Jul 2009.

[2] D. Li, et al., "Parallel-Detection Microwave Spectroscopy System for Breast Imaging," Rev Sci Instr, vol. 75, pp. 2305-2313, 2004.

[3] J. D. Shea, et al., "Three-Dimensional Microwave Imaging of Realistic Numerical Breast Phantoms Via a Multiple-Frequency Inverse Scattering Technique," Med Phys, vol. 37, pp. 4210-26, 2010.

[4] X. Li, et al., "An Overview of Ultra-Wideband Microwave Imaging Via Space-Time Beamforming for Early-Stage Breast-Cancer Detection," IEEE Antennas Propag Mag., vol. 47, pp. 19-34, Feb 2005.

[5] M. Klemm, et al., "Microwave Radar-Based Differential Breast Cancer Imaging: Imaging in Homogeneous Breast Phantoms and Low Contrast Scenarios," IEEE Trans Ant Propag, vol. 58, pp. 2337-2344, 2010.

[6] J. Bourqui, et al., "A Prototype System for Measuring Microwave Frequency Reflections from the Breast," Int J Biomed Imag, vol. 2012, 2012.

[7] M. Lazebnik, et al., "A Large-Scale Study of the Ultrawideband Microwave Dielectric Properties of Normal Breast Tissue Obtained from Reduction Surgeries," Phys Med Biol, vol. 52, pp. 2637-2656, May 21 2007.

[8] M. Lazebnik, et al., "A Large-Scale Study of the Ultrawideband Microwave Dielectric Properties of Normal, Benign and Malignant Breast Tissues Obtained from Cancer Surgeries," Phys Med Biol, vol. 52, pp. 6093-6115, Oct 21 2007.

[9] M. O'Halloran, et al., "Quasi-Multistatic Mist Beamforming for the Early Detection of Breast Cancer," IEEE Trans Biomed Eng, vol. 57, pp. 830-40, 2010.

[10] P. Kosmas and C. M. Rappaport, "A Matched-Filter Fdtd-Based Time Reversal Approach for Microwave Breast Cancer Detection," IEEE Trans Ant Propag, vol. 54, pp. 1257-64, 2006.

[11] S. Jacobsen and Y. Birkelund, "Improved Resolution and Reduced Clutter in Ultra-Wideband Microwave Imaging Using Cross-Correlated Back Projection: Experimental and Numerical Results," Int J Biomed Imag, vol. 2010, 2010.

[12] C. Gilmore, et al., "Microwave Biomedical Data Inversion Using the Finite-Difference Contrast Source Inversion Method," IEEE Trans Ant Propag, vol. 57, pp. 1528-1538, 2009.

[13] S. M. Salvador and G. Vecchi, "Experimental Tests of Microwave Breast Cancer Detection on Phantoms," IEEE Trans Ant Propag, vol. 57, pp. 1705-12, 2009.

[14] M. Haynes, et al., "Microwave Breast Imaging System Prototype with Integrated Numerical Characterization," Int J Biomed Imag, vol. 2012, 2012.

[15] M. Guardiola, et al., "3d Uwb Magnitude-Combined Tomographic Imaging for Biomedical Applications. Algorithm Validation," Radioeng, vol. 20, pp. 366-72, 2011.

[16] T. Henriksson, et al., "Quantitative Microwave Imaging for Breast Cancer Detection Using a Planar 2.45 Ghz System," IEEE Trans. Instru. Meas., vol. 59, pp. 2691-2699, 2010.

[17] P. M. Meaney, et al., "Clinical Prototype for Active Microwave Imaging of the Breast," IEEE Trans Microw Theory Tech, vol. 48, pp. 1841-1853, 2000.

[18] S. P. Poplack, et al., "Electromagnetic Breast Imaging: Average Tissue Property Values in Women with Negative Clinical Findings," Radiology, vol. 231, pp. 571-80, 2004.

[19] S. Poplack, et al., "Electromagnetic Breast Imaging: Pilot Results in Women with Abnormal Mammography " Radiology, vol. 243, pp. 350-359, 2007.

[20] T. M. Grzegorczyk, et al., "Fast 3-D Tomographic Microwave Imaging for Breast Cancer Detection," IEEE Trans Med Imaging, vol. 31, pp. 1584-1592, 2012.

[21] T. Henriksson, et al., "Clinical Trials of a Multistatic Uwb Radar for Breast Imaging," in 7th Loughborough Antennas and Propagation Conference, LAPC 2011, November 14, 2011 - November 15, 2011, Loughborough, UK, 2011.

[22] M. Klemm, "Contrast-Enhanced Breast Cancer Detection Using Dynamic Microwave Imaging," presented at the 2012 IEEE Int Symp Ant Propag and USNC-URSI Nat Radio Sci Mtg, Chicago, 2012.

[23] J. Bourqui, et al., "Balanced Antipodal Vivaldi Antenna with Dielectric Director for near-Field Microwave Imaging," IEEE Trans. Ant. Prop., vol. 58, pp. 2318-2326, 2010.

[24] E. C. Fear, et al., "Confocal Microwave Imaging for Breast Cancer Detection: Localization of Tumors in Three Dimensions," IEEE Trans. Biomed. Eng., vol. 49, pp. 812-822, 2002.

[25] T. C. Williams, Bourqui, J., Cameron, T.R., Okoniewski, M. and Fear, E.C., "Laser Surface Estimation for Microwave Breast Imaging Systems," IEEE Trans. Biomed. Eng., vol. 58, pp. 1193-1199, 2010.

[26] B. Maklad, et al., "Neighborhood-Based Algorithm to Facilitate the Reduction of Skin Reflections in Radar-Based Microwave Imaging," PIER B, pp. 115-139, 2012.

[27] J. M. Sill, and Fear, E.C. , "Tissue Sensing Adaptive Radar for Breast Cancer Detection: Experimental Investigation of Simple Tumor Models," IEEE Trans. Microw Theory Tech, vol. 53, pp. 3312-3319, Nov. 2005.

[28] J. Bourqui, et al., "Antenna Evaluation for Ultra-Wideband Microwave Imaging," Int J Ant Prop, p. 850149 (8 pp.), 2010.

[29] J. Bourqui, et al., "Measurement and Analysis of Microwave Frequency Signals Transmitted through the Breast," Int J Biomed Imag, vol. 2012, 2012.

[30] D. Kurrant and E. Fear, "Regional Estimation of the Dielectric Properties of Inhomogeneous Objects Using near-Field Reflection Data," Inverse Probl, vol. 28, p. 075001 (27 pp.), 2012.



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